The development of flexible zinc-ion batteries(ZIBs)faces a threeway trade-off among the ionic conductivity,Zn^(2+)mobility,and the electrochemical stability of hydrogel electrolytes.To address this challenge,we desig...The development of flexible zinc-ion batteries(ZIBs)faces a threeway trade-off among the ionic conductivity,Zn^(2+)mobility,and the electrochemical stability of hydrogel electrolytes.To address this challenge,we designed a cationic hydrogel named PAPTMA to holistically improve the reversibility of ZIBs.The long cationic branch chains in the polymeric matrix construct express pathways for rapid Zn^(2+)transport through an ionic repulsion mechanism,achieving simultaneously high Zn^(2+)transference number(0.79)and high ionic conductivity(28.7 mS cm−1).Additionally,the reactivity of water in the PAPTMA hydrogels is significantly inhibited,thus possessing a strong resistance to parasitic reactions.Mechanical characterization further reveals the superior tensile and adhesion strength of PAPTMA.Leveraging these properties,symmetric batteries employing PAPTMA hydrogel deliver exceeding 6000 h of reversible cycling at 1 mA cm^(−2) and maintain stable operation for 1000 h with a discharge of depth of 71%.When applied in 4×4 cm2 pouch cells with MnO_(2) as the cathode material,the device demonstrates remarkable operational stability and mechanical robustness through 150 cycles.This work presents an eclectic strategy for designing advanced hydrogels that combine high ionic conductivity,enhanced Zn^(2+)mobility,and strong resistance to parasitic reactions,paving the way for long-lasting flexible ZIBs.展开更多
Federated learning has revolutionized the way we approach machine learning by enabling multiple edge devices to collaboratively learn a shared machine learning model without the need for centralized data collection.Su...Federated learning has revolutionized the way we approach machine learning by enabling multiple edge devices to collaboratively learn a shared machine learning model without the need for centralized data collection.Such a new machine learning paradigm has gained significant attention in recent years due to its ability to address privacy and security concerns associated with centralized learning,as well as its potential to reduce communication overhead and improve scalability.展开更多
基金financially supported by the General Research Fund(CityU 11315622 and CityU 11310123)National Natural Science Foundation(NSFC 52372229 and NSFC 52172241)+3 种基金Green Tech Fund(GTF202220105)Guangdong Basic and Applied Basic Research Foundation(2024A1515011008)City University of Hong Kong(No.9020002)the Shenzhen Research Institute of City University of Hong Kong.
文摘The development of flexible zinc-ion batteries(ZIBs)faces a threeway trade-off among the ionic conductivity,Zn^(2+)mobility,and the electrochemical stability of hydrogel electrolytes.To address this challenge,we designed a cationic hydrogel named PAPTMA to holistically improve the reversibility of ZIBs.The long cationic branch chains in the polymeric matrix construct express pathways for rapid Zn^(2+)transport through an ionic repulsion mechanism,achieving simultaneously high Zn^(2+)transference number(0.79)and high ionic conductivity(28.7 mS cm−1).Additionally,the reactivity of water in the PAPTMA hydrogels is significantly inhibited,thus possessing a strong resistance to parasitic reactions.Mechanical characterization further reveals the superior tensile and adhesion strength of PAPTMA.Leveraging these properties,symmetric batteries employing PAPTMA hydrogel deliver exceeding 6000 h of reversible cycling at 1 mA cm^(−2) and maintain stable operation for 1000 h with a discharge of depth of 71%.When applied in 4×4 cm2 pouch cells with MnO_(2) as the cathode material,the device demonstrates remarkable operational stability and mechanical robustness through 150 cycles.This work presents an eclectic strategy for designing advanced hydrogels that combine high ionic conductivity,enhanced Zn^(2+)mobility,and strong resistance to parasitic reactions,paving the way for long-lasting flexible ZIBs.
文摘Federated learning has revolutionized the way we approach machine learning by enabling multiple edge devices to collaboratively learn a shared machine learning model without the need for centralized data collection.Such a new machine learning paradigm has gained significant attention in recent years due to its ability to address privacy and security concerns associated with centralized learning,as well as its potential to reduce communication overhead and improve scalability.
